## Fix Python – How do I initialize weights in PyTorch?

How do I initialize weights and biases of a network (via e.g. He or Xavier initialization)?
….

## Fix Python – Save classifier to disk in scikit-learn

How do I save a trained Naive Bayes classifier to disk and use it to predict data?
I have the following sample program from the scikit-learn website:
from sklearn import datasets
from sklearn.naive_bayes import GaussianNB
gnb = GaussianNB()
y_pred = gnb.fit(iris.data, iris.target).predict(iris.data)
print “Number of mis….

## Fix Python – How to implement the Softmax function in Python

From the Udacity’s deep learning class, the softmax of y_i is simply the exponential divided by the sum of exponential of the whole Y vector:

Where S(y_i) is the softmax function of y_i and e is the exponential and j is the no. of columns in the input vector Y.
I’ve tried the following:
import numpy as np

def softmax(x):
“””Compute softmax v….

## Fix Python – Convert array of indices to one-hot encoded array in NumPy

Given a 1D array of indices:
a = array([1, 0, 3])

I want to one-hot encode this as a 2D array:
b = array([[0,1,0,0], [1,0,0,0], [0,0,0,1]])

….

## Fix Python – What are logits? What is the difference between softmax and softmax_cross_entropy_with_logits?

In the tensorflow API docs they use a keyword called logits. What is it? A lot of methods are written like:
tf.nn.softmax(logits, name=None)

If logits is just a generic Tensor input, why is it named logits?

Secondly, what is the difference between the following two methods?
tf.nn.softmax(logits, name=None)
tf.nn.softmax_cross_entropy_with_logits….